Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
#load data
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
# It was told in the lecture that it is allowed to copy the same code for the first 3 exercises
df_2007 = df.query('year==2007')
df_2007_new = df_2007.groupby('continent').sum()
figure = px.bar(df_2007_new, x='pop', y=df_2007_new.index, text_auto='.2s', color=df_2007_new.index)
figure.update_layout(yaxis={'categoryorder': 'total ascending'})
figure.show()
figure = px.bar(df_2007_new, x='pop', y=df_2007_new.index, text_auto='.2s', color=df_2007_new.index)
figure.update_layout(yaxis={'categoryorder': 'total ascending'})
figure.show()
Add text to each bar that represents the population
figure = px.bar(df_2007_new, x='pop', y=df_2007_new.index, text_auto='.2s', color=df_2007_new.index)
figure.update_traces(textposition="outside")
figure.update_layout(yaxis={'categoryorder': 'total ascending'})
figure.show()
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
df_all = df.groupby(['continent', 'year']).sum().reset_index()
figure = px.bar(df_all, x='pop', y='continent', color='continent', animation_frame='year',
animation_group='continent', hover_name='continent', range_x=[0,4000000000])
figure.update_layout(yaxis={'categoryorder': 'total ascending'})
figure.show()
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
df_countries = df.groupby(['country', 'year']).sum().reset_index()
figure = px.bar(df_countries, x='pop', y='country', color='country', animation_frame='year',
animation_group='country', hover_name='country', range_x=[0,1400000000])
figure.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
figure.show()
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
figure = px.bar(df_countries, x='pop', y='country', color='country', animation_frame='year',
animation_group='country', hover_name='country', range_x=[0,1400000000], height=1000)
figure.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
figure.show()
figure = px.bar(df_countries, x='pop', y='country', color='country', animation_frame='year',
animation_group='country', hover_name='country', range_x=[0,1400000000],
range_y=[len(df_countries['country'].unique())-10.5, len(df_countries['country'].unique())-0.5])
figure.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
figure.show()